Andrew Gelman

According to our database, Andrew Gelman authored at least 39 papers between 1988 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Bayesian spatial modelling of localised SARS-CoV-2 transmission through mobility networks across England.

Thomas Ward, Mitzi Morris, Andrew Gelman, Bob Carpenter, William Ferguson, Christopher E. Overton, Martyn Fyles

PLoS Comput. Biol., November, 2023

Prediction scoring of data-driven discoveries for reproducible research.

Anna L. Smith, Tian Zheng, Andrew Gelman

Stat. Comput., 2023

Artificial Intelligence and Aesthetic Judgment.

Jessica Hullman, Ari Holtzman, Andrew Gelman

CoRR, 2023

Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach.

Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Pathfinder: Parallel quasi-Newton variational inference.

Lu Zhang, Bob Carpenter, Andrew Gelman, Aki Vehtari

J. Mach. Learn. Res., 2022

Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors.

Yuling Yao, Aki Vehtari, Andrew Gelman

J. Mach. Learn. Res., 2022

A fast regression via SVD and marginalization.

Philip Greengard, Andrew Gelman, Aki Vehtari

Comput. Stat., 2022

Delivering data differently.

Gwynn Sturdevant, A. Jonathan R. Godfrey, Andrew Gelman

CoRR, 2022

The Worst of Both Worlds: A Comparative Analysis of Errors in Learning from Data in Psychology and Machine Learning.

Jessica Hullman, Sayash Kapoor, Priyanka Nanayakkara, Andrew Gelman, Arvind Narayanan

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021

Reviews.

Darren B. Glass, Béla Bajnok, Carolyn Yackel, Edray Goins, Jenna P. Carpenter, Stephen Kennedy, Jeanette Shakalli, Ursula Whitcher, Dave Kung, Kathryn Kozak, Robert Ghrist, Andrew Gelman

Am. Math. Mon., 2021

Accounting for uncertainty during a pandemic.

Jon Zelner, Julien Riou, Ruth Etzioni, Andrew Gelman

Patterns, 2021

Toward a Taxonomy of Trust for Probabilistic Machine Learning.

Tamara Broderick, Andrew Gelman, Rachael Meager, Anna L. Smith, Tian Zheng

CoRR, 2021

To design interfaces for exploratory data analysis, we need theories of graphical inference.

Jessica Hullman, Andrew Gelman

CoRR, 2021

Bayesian hierarchical stacking.

Yuling Yao, Gregor Pirs, Aki Vehtari, Andrew Gelman

CoRR, 2021

2020

Expectation Propagation as a Way of Life: A Framework for Bayesian Inference on Partitioned Data.

Aki Vehtari, Andrew Gelman, Tuomas Sivula, Pasi Jylänki, Dustin Tran, Swupnil Sahai, Paul Blomstedt, John P. Cunningham, David Schiminovich, Christian P. Robert

J. Mach. Learn. Res., 2020

A Fast Linear Regression via SVD and Marginalization.

Philip Greengard, Andrew Gelman, Aki Vehtari

CoRR, 2020

2018

Yes, but Did It Work?: Evaluating Variational Inference.

Yuling Yao, Aki Vehtari, Daniel Simpson, Andrew Gelman

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Erratum to: Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC.

Aki Vehtari, Andrew Gelman, Jonah Gabry

Stat. Comput., 2017

Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC.

Aki Vehtari, Andrew Gelman, Jonah Gabry

Stat. Comput., 2017

Automatic Differentiation Variational Inference.

Alp Kucukelbir, Dustin Tran, Rajesh Ranganath, Andrew Gelman, David M. Blei

J. Mach. Learn. Res., 2017

The Prior Can Often Only Be Understood in the Context of the Likelihood.

Andrew Gelman, Daniel Simpson, Michael Betancourt

Entropy, 2017

A Safe Depth Forecasting Model for Insuring Tubewell Installations Against Arsenic Risk in Bangladesh.

Matilde Trevisani, Jie Shen, Alexander van Geen, Andrew Gelman, Shuky Ehrenberg, John Immel

Proceedings of the Computational Science and Its Applications - ICCSA 2017, 2017

The statistical significance filter leads to overconfident expectations of replicability.

Shravan Vasishth, Andrew Gelman

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2016

Centralized Analysis of Local Data, with Dollars and Lives on the Line: Lessons from the Home Radon Experience.

Phillip N. Price, Andrew Gelman

Proceedings of the Computational Social Science: Discovery and Prediction, 2016

2015

Simulation-efficient shortest probability intervals.

Ying Liu, Andrew Gelman, Tian Zheng

Stat. Comput., 2015

Automatic Variational Inference in Stan.

Alp Kucukelbir, Rajesh Ranganath, Andrew Gelman, David M. Blei

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Understanding predictive information criteria for Bayesian models.

Andrew Gelman, Jessica Hwang, Aki Vehtari

Stat. Comput., 2014

The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo.

Matthew D. Hoffman, Andrew Gelman

J. Mach. Learn. Res., 2014

The Mythical Swing Voter.

David Rothschild, Sharad Goel, Andrew Gelman, Doug Rivers

CoRR, 2014

2012

In praise of the referee

Nicolas Chopin, Andrew Gelman, Kerrie L. Mengersen, Christian P. Robert

CoRR, 2012

2009

Commentary - Discussion of the Article "Website Morphing".

Andrew Gelman

Mark. Sci., 2009

2007

Weighted Classical Variogram Estimation for Data With Clustering.

Cavan Reilly, Andrew Gelman

Technometrics, 2007

Manipulating and summarizing posterior simulations using random variable objects.

Jouni Kerman, Andrew Gelman

Stat. Comput., 2007

2006

Bayesian Measures of Explained Variance and Pooling in Multilevel (Hierarchical) Models.

Andrew Gelman, Iain Pardoe

Technometrics, 2006

Multilevel (Hierarchical) Modeling: What It Can and Cannot Do.

Andrew Gelman

Technometrics, 2006

An experimental study of storable votes.

Alessandra Casella, Andrew Gelman, Thomas R. Palfrey

Games Econ. Behav., 2006

2000

Bayesian probabilistic extensions of a deterministic classification model.

Iwin Leenen, Iven Van Mechelen, Andrew Gelman

Comput. Stat., 2000

Type S error rates for classical and Bayesian single and multiple comparison procedures.

Andrew Gelman, Francis Tuerlinckx

Comput. Stat., 2000

1988

FRM: An Intelligent Assistant for Financial Resource Management.

Andrew Gelman, Susan Altman, Matt Pallakoff, Ketan Doshi, Catherine Manago, Thomas C. Rindfleisch, Bruce G. Buchanan

Proceedings of the 7th National Conference on Artificial Intelligence, 1988